Generally, image signals obtained from an imaging system having imaging devices and their accompanying analog circuits, A/D converters, etc., contain noise components. The noise components can be categorized roughly into fixed pattern noise and random noise. The fixed pattern noise is noise, such as defective pixels, caused mainly by imaging devices. On the other hand, the random noise is generated in imaging devices and analog circuits, and has characteristics close to white noise.
An example of noise reduction processing of random noise in motion pictures is cyclic type noise reduction processing using the correlation characteristics in the direction at the time axis. The cyclic type noise reduction processing uses the characteristics of high correlation of the image signal of the present with the image signals of the past, whereas the correlation of random noise with the image signals of the past is low, and thereby, extracts only the random noise by performing differential processing between the present and the past image signals, and performs noise reduction processing for the present image signal using the extracted random noise.
In this case, there is a problem in that if the differential processing is performed in moving areas where the object of shooting moves, the motion components are also extracted together with the random noise. For this reason, the accuracy in removing the motion component from the signal which underwent the differential processing becomes the cause to affect the accuracy of the cyclic type noise reduction processing.
An example of the method of removing such a motion component is JP10-13734A, which discloses a method for detecting a motion component from the image signal and for controlling a limit value and a feedback coefficient for the signal which underwent the differential processing based on the detected motion component. Thereby, when there are few number of motion components, the noise reduction processing is performed strongly to obtain image signals having low amount of noise, and when there are large number of motion components, the noise reduction processing is performed weakly to obtain image signals having little afterimage.
Moreover, JP2000-209507A discloses a method for controlling a feedback coefficient from the signal value that underwent the differential processing. If the value of the signal which underwent the differential processing is small, it is determined as the random noise, and it is possible to obtain an image signal having small amount of noise by making the feedback coefficient larger. If the value of the signal which underwent the differential processing is large, it is determined as the motion component, and it is possible to obtain image signals having little afterimage by making the feedback coefficient small.
Furthermore, JP2006-23959A discloses an example for controlling noise reduction processing in block unit basis by presuming the amount of noise in block unit basis based on noise models.